#loop engineering
2832 related articles
Product Reviews·3 min
AutoGPT: A Deep Dive into the Open-Source AI Agent Platform with 180K Stars
Deep dive into the AutoGPT open-source project, covering its autonomous AI agent architecture, core features, use cases, and future development. Learn how this 184K-Star GitHub project makes autonomous AI accessible to everyone.
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Tech Frontiers·2 min
DeadEnd-CLI: Open-Source AI Penetration Testing Tool Achieves 81% Pass Rate on Black-Box Benchmark
DeadEnd-CLI is an open-source AI agentic penetration testing tool achieving 81% full black-box pass rate on the XBOW benchmark using KIMI K2.5, with multi-model support and self-hosted deployment.
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Tutorials·4 min
Dify AI Agent Tutorial: Build Tool-Calling & Smart Search with Zero Code
Learn how to build an AI Agent on Dify with zero code, covering Function Call vs ReAct modes, Exa search tool setup, time-awareness solutions, and Agent best practices.
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Tutorials·3 min
GPT-Realtime-2 Standup Automation: A Practical Guide to Voice-Driven Ticket Management
Explore how GPT-Realtime-2 enables standup automation by using voice AI and Function Calling to automatically convert verbal reports into Jira and Linear ticket operations.
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Deep Dives·4 min
Context Engineering Explained: The AI Paradigm Shift from Prompt to Context Engineering
Deep dive into Context Engineering: its core principles and practices. From Prompt Engineering to context design, orchestration, and optimization—exploring how Karpathy's new AI paradigm reshapes LLM app development and AI Agent construction.
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Product Reviews·3 min
Cube Studio: A Comprehensive Analysis of Tencent's Open-Source Cloud-Native AI Platform
Deep dive into Tencent Music's open-source Cube Studio cloud-native AI platform, covering distributed training, LLM fine-tuning & inference, Pipeline orchestration, and domestic hardware adaptation.
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Deep Dives·4 min
Kortix Open-Sources Agent Computer Use: A Rust-Powered CLI Tool for AI Computer Control
Kortix AI open-sources Agent Computer Use, a high-performance Rust CLI tool enabling AI agents to control computers. Explore its architecture, advantages over Anthropic's Claude Computer Use, and future of open-source computer control tools.
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Product Reviews·3 min
awesome-LLM-resources: A Deep Dive into GitHub's 8K-Star Comprehensive LLM Learning Resource Repository
Deep dive into awesome-LLM-resources, a GitHub 8K-star project covering multimodal AI, AI Agents, MCP protocol, model training/inference, and AI coding tools — a one-stop LLM learning guide.
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Tech Frontiers·3 min
LangGraph Multi-Agent Company Research Tool: A Practical Guide to Open-Source AI Due Diligence
Deep dive into the open-source company-research-agent: LangGraph multi-agent architecture + Tavily search + dual-LLM collaboration for automated company due diligence and competitive intelligence.
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Deep Dives·4 min
Agent, MCP, and Function Calling: A Complete Guide to Their Differences and Relationships
A deep dive into the relationships between AI Agent, MCP protocol, Function Calling, and Prompt. From basics to full architecture, build a clear cognitive framework for AI app development.
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Tech Frontiers·2 min
Codex Adds OpenAI Developers Plugin — Building AI Apps with AI Just Got Easier
OpenAI Codex adds the Developers plugin, letting developers directly access OpenAI API docs and best practices to rapidly build AI Agents and smart apps.
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Tech Frontiers·3 min
OpenAI Codex Adds Computer Use: AI Agents Autonomously Control Mac in the Background
OpenAI adds Computer Use to Codex, enabling AI agents to autonomously click, type, and operate across Mac apps in the background without taking user control.
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Deep Dives·3 min
Claude's Advisor Strategy: Small Models Execute, Large Models Supervise — A New Cost-Saving Paradigm for AI Agents
Anthropic's Advisor Strategy lets Sonnet execute tasks while Opus serves as advisor, cutting costs 12% while boosting SWE-Bench by 2.7 points. A new multi-model AI Agent paradigm explained.
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Expert Opinions·3 min
Surviving the AI Layoff Wave: The Workplace Hype Truths Exposed by a Satirical Video
Mo Bitar's satirical TikTok exposes AI workplace absurdities: fake jargon to secure budgets, automating colleagues for promotions. A deep dive into overestimated AI capabilities, fear-driven decisions, and the moral cost of tech hype.
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Tutorials·3 min
Claude Code Domestic Alternative: Low-Cost Deployment and Six Core Architecture Components Explained
Detailed guide on deploying Claude Code domestic alternatives via compatible API interfaces. Deep dive into six core systems: built-in tools, hierarchical memory, multi-Agent collaboration, and more.
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Industry Insights·3 min
AI-Native Engineering Transformation: Real Emotions and Coping Strategies from 218 Technical Leaders
Based on research with 218 engineering leaders, this deep dive explores the contradictory emotions in AI-native transformation — excitement and anxiety coexisting — and how leaders navigate successful change.
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Tutorials·3 min
AI Project Evaluation Framework: A Practical Guide to 5 Levels and 30 Key Metrics
A battle-tested AI project evaluation framework covering 5 levels and 30 core metrics—model quality, UX, system efficiency, business value, and data loops—to scientifically assess LLM Agent performance.
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Tutorials·3 min
Andrew Ng's New Course: A Practical Guide to Data Governance for Enterprise AI Agents
Andrew Ng and Databricks launch an AI Agent data governance course covering least privilege principles, Unity Catalog permissions, MLflow tracing, and a complete governance lifecycle from build to deployment. Free to learn.
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Expert Opinions·2 min
AI Coding Tools ≠ Development Transformation: How Engineering Teams Can Truly Restructure the Software Development Lifecycle
Adopting AI coding tools isn't the same as transforming how you build. Learn how engineering teams can restructure their SDLC around AI for true competitive advantage.
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Product Reviews·3 min
AGENTS.md Coding Rules Put to the Test: Code Quality Unchanged, Development Efficiency Significantly Improved
A developer tested AGENTS.md coding rules across 40 PRs on three AI coding Agents. Results: code quality unchanged, but fewer tool calls, faster completion, and lower costs.
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